This survey focuses on critical role of machine learning in developing Human Activity Recognition applications based on inertial sensors in conjunction with physiological and environmental sensors.
The first ever study to use urinary cellular gene expression to study sepsis. Researchers identified alterations in gene expression unique to systemic and kidney-specific pathophysiologic processes using whole-genome analyses of RNA isolated from the urinary cells of sepsis patients.
Among critically ill surgical sepsis patients, persistent AKI and the absence of renal recovery are associated with distinct early and sustained immunologic and endothelial biomarker signatures and decreased long-term physical function and survival.
Audiovisual modules may improve knowledge and comprehension of commonly performed ICU procedures among critically ill patients and caregivers who have no healthcare background.
In this paper, the problem of mining complex temporal patterns in the context of multivariate time series is considered. A new method called the Fast Temporal Pattern Mining with Extended Vertical Lists.
Patients and physicians make essential decisions regarding diagnostic and therapeutic interventions. These actions should be performed or deferred under time constraints and uncertainty regarding patients’ diagnoses and predicted response to treatment. This may lead to cognitive and judgment errors.